code: def download_w2v(model_url, dir_path):
      os.makedirs(dir_path, exist_ok=True)
  
      model_name = model_url.split("/")[-1]
      model_path = os.path.join(dir_path, model_name)
  
      dict_url = (
          "https://dl.fbaipublicfiles.com/fairseq/wav2vec/dict.ltr.txt"
      )
      dict_path = os.path.join(dir_path, dict_url.split("/")[-1])
  
      with FileLock(model_path + ".lock"):
          if not os.path.exists(model_path):
              torch.hub.download_url_to_file(model_url, model_path)
              torch.hub.download_url_to_file(dict_url, dict_path)
              logging.info(f"Wav2Vec model downloaded {model_path}")
          else:
              logging.info(
                  f"Wav2Vec model {model_path} already exists."
              )
  
      return model_path
  
file_path: espnet/espnet2/asr/encoder/wav2vec2_encoder.py
imports: import contextlib
  import copy
  import logging
  import os
  from typing import Optional, Tuple
  import torch
  from filelock import FileLock
  from typeguard import check_argument_types
  from espnet2.asr.encoder.abs_encoder import AbsEncoder
  from espnet.nets.pytorch_backend.nets_utils import make_pad_mask
  from espnet.nets.pytorch_backend.transformer.layer_norm import LayerNorm
label_desc: Use image node_id 1 for calling a global function with example usage: download_w2v(model_url, dir_path) and returns: model_path